Research Article
General Science
Environmental Assessment
Environmental Assessment

The spatial variability of heavy metals concentrations and sedimentary organic matter in estuary sediment of Sungai Perlis, Perlis, Malaysia

Jamil T1, Lias K1, Hanif HF1, Norsila D1, Aeisyah A1, Kamaruzzaman BY2

Abstract

A study of the relationship between heavy metals and sedimentary organic matter in estuary sediments was carried out along Sungai Perlis during the Southwest monsoon (May-July 2011), and Northeast monsoon (November 2011-January 2012). Results indicate that, for all seasons, the concentration of As ranged from 11.88 to 59.12 µg/g in dry weights, Cd from 0.02 to 0.17 µg/g in dry weights, Cr from 56.67 to 158.23 µg/g in dry weights, Cu from 10.22 to 34.47 µg/g in dry weights, Pb from 31.19 to 70.62 µg/g in dry weights and Zn from 61.29 to 121.10 µg/g in dry weights. The average distribution trend of heavy metals along Sungai Perlis is as follows; Cr > Zn > Pb > As > Cu > Cd. Meanwhile, the percentage value of organic matter content in sediments seemed to be slightly higher during the Southwest Monsoon compared to the Northeast Monsoon, with the values of 7.43 ± 1.55% and 6.75 ± 1.72%, respectively. The relationship between heavy metal concentrations and organic matter for all seasons and stations was proven statistically via Pearson’s Correlation Analysis. Results revealed that all metals except for As and Cu, correlate significantly with the p-value of below 0.05. According to Principal Component Analysis (PCA), all metals can be defined as an anthropogenic component. However, the sediment quality guidelines (SQG) proved that, Cd and Zn in sediment of Sungai Perlis were below from the threshold values. While, the concentrations of Arsenic from this study area may be considered as a serious threat for aquatic organism and also human health.

Keywords Heavy Metals, Organic Matter, Pearson’s Correlation, Estuary Sediment.

Author and Article information

Author info
1 Ocean Research, Conservation & Advances (ORCA), Division of Research, Industrial Linkage, Community Network & Alumni, Universiti Teknologi MARA (Perlis), 02600 Arau, Perlis, Malaysia.
2 Institute of Oceanography and Maritime Studies, International Islamic University Malaysia, Jalan Sultan Ahmad Shah, Bandar Indera Mahkota, 25200, Kuantan, Pahang, Malaysia

RecievedSep 13 2013  AcceptedJan 21 2014  PublishedFeb 26 2014

CitationJamil T, Lias K, Hanif HF, Norsila D, Aeisyah A, Kamaruzzaman BY (2014) The spatial variability of heavy metals concentrations and sedimentary organic matter in estuary sediment of Sungai Perlis, Perlis, Malaysia. Science Postprint 1(1): e00016. doi: 10.14340/spp.2014.02A0003

Copyright©2014 The Authors. Science Postprint is published by General Healthcare Inc. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 2.1 Japan (CC BY-NC-ND 2.1 JP) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

FundingThese researches are fully funded by Ministry Of Science and Technology (MOSTI, Malaysia) under Fundamental Research Grant Scheme (FRGS).

Competing interestsThere is no competing interests. Our institution is located at northern part of peninsular Malaysia and closed to the Andaman Sea. There is no research institution carried out this kind of research activities.

Donation message This research is carried out at Sungai Perlis Estuaries, Perlis, Malaysia which is close to Andaman Sea. According to sediment quality guidelines (SQG) proved that, the concentrations of Arsenic from this study area may be considered as a serious threat for aquatic organism and also human health. Based on our previous study on the accumulation of heavy metal in the Marcia Marmorata sp found that the mean concentration of Arsenic (As), Cadmium (Cd) and Copper (Cu) in the tissue was exceeded the permissible limit except for Zinc (Zn) when compared to the FAO/WHO 2004 as well as Food Regulation 1985. Therefore it can be generalized that Marcia Marmorata sp. from the Coastal area of Sungai Perlis Estuary are not safe to consume in terms of these heavy metal concentration and constitute a risk for human health. Therefore future study is crucial and need to be carried out for the heavy metals accumulation in human body to quantify the health impact of these toxic metals.
The significance of this study would be very beneficial in providing database to government and non government agency to develop this area. This assessment also, would be providing valuable information for local citizens and Asian neighboring country such as Thailand and Indonesian.

Corresponding authorJamil Tajam
AddressOcean Research, Conservation & Advances (ORCA), Division of Research, Industrial Linkage, Community Network & Alumni, Universiti Teknologi MARA (Perlis), 02600 Arau, Perlis, Malaysia
E-mailIf you want to contact author,Please register as a member.

Introduction

Nowadays, environmental problems have garnered significant amounts of attention due to the problems of environmental contamination caused by heavy metals 1. Heavy metals are one of the natural components of the earth’s crust that can enter the water cycles through a variety of processes. The pollution that comes out from heavy metals has called out for an increasing awareness worldwide due to a dramatic increase of anthropogenic heavy metals to the ecosystems through air, water and soils. Most previous studies showed that heavy metals are among the most common environmental pollutants due to its toxicity, persistence, and non-degradable characteristics in the environment 2.
The toxicity of heavy metals has long been of great concern since it is very important to the health of people and ecology 3. Heavy metals are of the major concern due to their persistent and bio-accumulative nature. According to Kim et al., (2002) and Lee et al., (2001), heavy metals are one of the pollutants that contribute to serious adverse effects to aquatic pollution 4, 5. These elements may be discharged through anthropogenic sources and later accumulate in receiving systems such as sediments, soil and water. Heavy metals are non-degradable and very harmful to plants, aquatic organisms and humans at certain levels of exposure 6.
Accumulation of heavy metals in sediments is largely controlled by their geochemistry such as type and quantities of organic matter, grain size and cation exchange capacity 7. The burial of organic matter in margin sediments provides the primary long-term sink for reduced carbon in the ocean 8. River-dominated margins are quantitatively important sites for organic matter accumulation, where its organic matter content becomes a crucial factor in determining the extent of sorption 9.
The distribution of heavy metals in sediments approves of the influences of anthropogenic sources giving impact on aquatic ecosystems 10. The organic matter may influence the site of deposition of metals due to its ability of adsorption, and this leads to strong correlation between it and metal elements 11. As mentioned by Wang and Chen (2000), the organic matter content is a more important factor compared to grain size in controlling the distribution of trace metals in the sediments 12. The different mobility of each sediment fraction may influence the trace metal distribution accumulating in sediments 13.
Therefore, Sungai Perlis Estuary in Perlis is a good example of a site where human pressures and natural values compete with each other. The river basin is approximately 310 km2 with its length of about 11 km through Kangar city to Kuala Perlis, Perlis, Malaysia. Sungai Perlis is classified as a Class III river, which is currently experiencing heavy erosion at its banks, and has become very shallow (Figure 1). Rubbish thrown into the river is therefore very visible and it is not accessible to boats. There is also a former landfill located in Kuala Perlis. This directly affects the water quality of the river, while contributing to the increment of sediment contamination. Other pollution point sources include shrimp livestock ponds, Kangar wet market, food stalls, and the Kuala Perlis Fisherman Jetty. Due to these geographic changes, the research will serve as a guideline needed prior to the development of the Sungai Perlis as a developing area. One of the aims of this study is to investigate the correlation between heavy metal and organic matter. This study will give a better understanding between the linkage of heavy metals and organic matter, which can also be a future reference for sedimentation data in Sungai Perlis.

Materials and Methods

Study area

Generally, Sungai Perlis was located at latitude of 6°22'60 N and longitude of 100°17'60 E, Northern part of Malaysia (Figure 1). There were ten stations established along the Sungai Perlis  during Southwest monsoon (May-July 2011), and Northeast monsoon (November 2011-January 2012), and were marked using the Global Positioning System (Table 1). These locations were selected based on the fact that they might have been impacted by the nearby source of contamination. Generally, all stations have a lot of human activities such as fish landing port (St. 4), fisherman village (St. 5 and 6), former landfill (St. 7), Shrimp aquaculture (St. 8 and 9) and Paddy field (St. 10) Surface sediment samples (1-5cm) were collected using the Van Veen Grab. Most samples collected tend to have gray to brown coloration, which indicate the samples were mainly consist the mixture of silt and clay. Some samples observed consist of sea shells and dead leaves. Afterwards, collected samples were placed in plastic bags which were previously immersed in 5% nitric acid for two to three days to prevent sample contamination. The sediment samples were then preserved in the icebox at 4°C to maintain the original condition of the samples. At the laboratory, samples were dried in the oven at 105°C for 24 hours. For heavy metal and organic matter analysis, it was ensured that the samples should be completely dried before grinding the samples with mortar and pestle, and later sieved under 63 µm. Precautions in preventing sample contamination were given priority. Samples were then stored in labelled plastic vials and kept in the drying cabinet until lab analysis.

Figure 1 Map of Sungai Perlis, Malaysia

Table 1 The sampling coordinates of Sungai Perlis, Malaysia

Sample Digestion

In this study, the digestion of samples and analytical procedures were adopted and applied from that of Tsugonai and Yamada (1980), Kamaruzzaman (1999) and Jamil (2006) with little modifications 14, 15, 16. For this analysis, 0.05 g of the fine powder sediment (<63 μm) was weighed and put into a Teflon vessel. After that, 1.5 ml of mixed acid (2.5 HF: 3 HNO3: 3 HCL) was added into the Teflon vessels using a single channel pipette, 100-1000 micro litre (μl) of the brand CappAero which was ISO 9001; 2000 certified. This digestion method is also known as the aqua regia + HF digestion method, which was also applied by Trimm et al. (1998) and Chen and Ma (2001) 17, 18. Finally, the Teflon Bomb jackets were screwed tightly to prevent the appearance of silicate gel on their bodies, before placing the Teflon Bombs into the oven for 6 hours at 160℃. After 6 hours, they were cooled down under room temperature where after that, 3.0 ml of acid solution composed of ethlenediaminetetraacetics acid (EDTA) and Boric acid were added. The samples were then again put into the oven at 160℃ for another 6 hours. The clear solution obtained was transferred into centrifuge tubes and meshed-up to 10 ml with Mili-Q water. To verify the precision of the analytical procedures, the sediment samples were analysed in three replicates for each sampling point and a sample blank. While, to confirm analytical accuracy, portions of certified reference materials (SRM1646a - estuarine sediments) from the National Institute of Standards and Technology (NIST) were analysed with each batch of samples.  Then, PerkinElmer® SCIEX® ELAN® 9000 ICP-MS was used to determine the concentrations of metals (Cd, Co, Fe, Pb and Zn) in the final digested solutions.

Determination of organic matter

For this analysis, methods of loss upon ignition notion were used. These methods were applied based on ASTM D 2974 - Standard Test Method for Moisture, Ash and Organic Matter of Peat and Organic Soils. 1 g of fine soils was dried in the oven at 105℃ for 2 hours. This process is prolonged until a constant weight was achieved. The weight of empty and dried porcelain dish (MP) was measured and recorded prior to placing 1 g of fine soils (<63 mm) into the dish and re-weighing the dish (MPDS). The porcelain dish was later placed inside the muffle furnace, where the temperature was gradually increased to 440℃. The dish was then left to burn overnight inside the furnace. On the next day, the dish was taken out to cool at room temperature before it was reweighed for its ash content (MPA). 

% Organic matter = (MO /MD) × 100
Where, MO = mass of organic matter, MO = MD - MA
MA = mass of ashed soil, MA = MPA - MP
MD = mass of dry soil, MD = MPDS -MP

Results

For method validation, Certified Reference Material (SRM1646a) was determined as a precision check. The percentage of recoveries (n = 6 for each metal) for certified and measured concentration of those metals was satisfactory, with the recoveries being 81.67–96.15%. Table 2 shows the recovery test results for SRM (1646a) analysis.

Table 2 Recovery test results (concentration for all metals are in μg/g dry weight)

From this study, the heavy metal contents of the sediment were analysed and the results were depicted in Table 3, Figure 2 and Figure 3. According to this study, the concentration of all elements along the stations was found to be constantly increasing toward the upstream area for both seasons. The highest values were recorded at the areas close to the aquaculture activities, paddy field outlets and the domestic area (St. 8, 9 and 10). As for seasonal comparison, during the Southwest Monsoon (SWM), Zn recorded the highest value of heavy metal concentration with the average value of 94.45 ± 18.57 μg/g in dry weight, followed by Cr, Pb, Cu, and As with the average concentration of 93.09 ± 18.35 μg/g in dry weight, 39.22 ± 8.18 μg/g in dry weight, 23.63 ± 8.87 μg/g in dry weight, and 19.74 ± 5.86, μg/g in dry weight, respectively. However, the concentration of Cd in the study area was indicated to be slightly higher in some stations (particularly St. 8) with the value of 0.21 μg/g in dry weight. Meanwhile, during the NEM season, heavy metal distribution trends seem to have changed, where some of the heavy metals recorded slightly higher concentrations compared to the SWM season, except for Cd, Cu, and Zn. From the results, the concentration of Cr was found to be the highest among other metals with the average value of 112.83 ± 25.81 μg/g in dry weight. According to statistical analysis (one-way ANOVA), As, Cr, and Pb concentrations were significantly different between the seasonal changes, with the p-value below 0.05. Other than that, all metals showed insignificant differences between sampling stations. In general, the average trend of mean concentration of heavy metals in Sungai Perlis, Malaysia during SWM and NEM seasons can be expressed as Zn > Cr > Pb > Cu > As > Cd and Cr > Zn > Pb > As > Cu > Cd, respectively.

Table 3 Data for heavy metal and organic matter (concentration of heavy metal is in μg/g dry weight while the organic matter is in percentage)

a : minimum value, b : maximum value, SWM: Southwest Monsoon, NEM: Northeast Monsoon

Figure 2 Surface profile of As (a), Cd (b) and Cr (c) distribution during SWM and NEM seasons

Figure 3 Surface profile of Cu (a), Pb (b) and Zn (c) distribution during SWM and NEM seasons

Moreover, regarding to Figure 4, the percentage of organic matter content (OM) of sediment recorded a slightly higher value during the SWM season (7.43 ± 1.55%) compared to the NEM season (6.75 ± 1.72 %) with a difference of 0.68%. The highest percentage value of OM was found at St.8 during the SWM season with a value of 9.08%, while the lowest percentage value was obtained at St.1 (4.93%). However, during the NEM season, the highest and lowest percentages of OM were recorded at St.10 (8.30%) and St.3 (3.88%), respectively. Statistical analysis (one-way ANOVA) showed no significant differences between both seasons, however, there were significant differences between sampling stations.

Figure 4 Surface profile of organic matter (%) distribution during SWM and NEM seasons

Discussion

According to Macalady and Ranville (1998), natural organic matter is complex and may have unique combinations of functional groups 19. The quantity of organic matter transported by rivers is well-documented 20, 21. The major source of organic matter can be derived from anthropogenic activities (e.g. domestic, agricultural and industrial wastes) which are difficult to quantify but likely contribute significantly to the global budget 22. The estimation of organic matter can be made by observing the anthropogenic activities that present in the study area. The organic material distribution in estuary systems and rivers tends to be dissimilar. The concentration of organics in water or bottom sediments is influenced by natural and anthropogenic sources. Besides, the complex behaviour of estuaries resulted from many processes including physical, chemical, and biological, can cause differences in the distribution of organics.

The distribution of heavy metals in sediments approves of the influences of anthropogenic sources give impact on aquatic ecosystems 10. The organic matter decides the site of deposition of metals due to its ability of adsorption, which leads to strong correlation between it and metal elements 11. As mentioned by Wang and Chen (2000), the organic matter content is a more important factor than grain size in controlling the distribution of trace metals in the sediments 12. The different mobility of each sediment fraction can influence the trace metal distribution accumulating in sediments 13. On the other hand, heavy metals also generally have significant correlation with OM content 23, 24. Veeh (1967) and Jones (1974) reported that organic matter can act as an agent to trap metals within the sediment 25, 26.

The significant relationships between concentration of heavy metals and OM content were further established by performing Pearson’s correlation analysis (Table 4 and Figure 5). From the observation, Cd and Zn were positively correlated strongly with the ‘r-value’ of 0.716 and 0.701, respectively. Statistical analysis revealed the strong binding of OM with heavy metals in the study area.  In general, the high percentage of organic material in these sediments is believed to have originated from anthropogenic sources. The accumulation of OM will increase the probability of high concentrations of heavy metals deposited in the study area. According to Chou et al. (2002), heavy metal concentrations were found to be higher when the total organic matter content was high in sediments 27.

Table 4 Pearson's Correlation Matrix between organic matter and heavy metals

*: Correlation is significant at the 0.05 level (2-tailed), **: Correlation is significant at the 0.01 level (2-tailed).

Figure 5 Pearson’s correlation between heavy metals and organic matter

From the observation, stations that are in the upstream area (St.7–10) showed the highest average values for Cd, Zn and OM percentage. This is most probably due to the aquaculture activities and the use of fertilizers in agriculture processes (paddy field). Wastes, often untreated, from aquaculture farms and paddy fields discharged directly into the surrounding aquatic environment often contain antibiotics, pesticides and fertilizers. According to Chou et al. (2002), heavy metals, particularly zinc, accumulate on riverbeds that are not far from aquaculture farms 27. Moreover, Burridge et al. (1999) stated that Cd accumulation can exceed 0.7 mg·g-1 in the sediment near the aquaculture farms 28.

On the other hand, the other anthropogenic sources of Zn and Cd in sediment are fertilizers 29. From the observation, at present, farmers in this area have used fertilizer trace elements, consisting of Zn (16%), B (2.5%), Cu (0.5%), Fe (2%), Mn (5%), Mo (0.1%) and Si (5%) for their paddy. The high percentage of Zn present in the fertilizer may have a great impact on the Zn distribution in the study area. While according to Finnish Ministry of Agriculture and Forestry (2000), Cd can be present in this study area, which might originate from phosphorus-fertilizers, atmospheric deposition, animal manures, and to a smaller extent, liming agents, sewage sludge and bio-waste 30. Lu et al. (1992) reported that the phosphate fertilizers were generally the major source of trace metals among all inorganic fertilizers, and much attention had also been paid to the concentration of Cd in phosphate fertilizers 31. A great majority of agricultural soils in Malaysia are heavily fertilized by this kind of fertilizers, reported Zarcinas et al. (2004) 32. According to Habibah et al. (2011), the total Cd concentration in paddy soil samples collected from Yan, Kota Setar, Kubang Pasu and Bumbung Lima ranged from 3.54 to 20.86 mg/kg 33.

Furthermore, weathering processes of dolomite or limestone played an important role in increasing the anthropogenic sources of heavy metals especially Zn. The areas that are underlain by limestone of varying age, most of which will host lead/zinc/silver mineralization, intermingled with three major granitic intrusive belts 34. According to Price (2011), Perlis is a small state in northern Malaysia, and it has both isolated tower karst hills as well as a long range of limestone hills 35. Apart from that, the possible sources of Zn in the study area are from domestic waste, shipyard, automotive and industrial effluents. Moreover, household products including powder and liquid laundry detergents, shampoos, toilet tissue papers and other cleaning products may also contribute to the zinc load into the aquatic environment 36.

For Cr and Pb, Pearson’s correlation showed significant correlations, where the ‘r-value’ for both elements were 0.515 and 0.446, respectively (Table 4). This indicates that the relationship between these elements and OM was on medium level. From these observations, the presence of Cr in this area is possibly due to the renovation of irrigation canal gate that was conducted close to St.10.  It is believed that the cement used in this renovation process earlier was leached by rainwater or flushed down via river runoff, where this element later settles down at the bottom sediment. According to ATSDR (2008), the environmental sources of chromium are mainly from cement dust (cement contains chromium), the wearing down of asbestos linings that contain chromium, emissions of chromium-based automotive catalytic converters, and tobacco smoke 37. During NEM, rainfall may frequently wear down the asbestos lining at the house's wall and enter the drainage system which leads into the river. The drainage system of residential areas that can be found nearby St 8 is believed to be one of the Cr sources due to the asbestos lining. Other than that, the chromium source in aquatic ecosystems is domestic wastewater effluents with the percentage value of 32.2% in total 38

Residual lead (Pb) in water also contributes to lead exposure in this study area. These residuals were expected to have come from the small shipyard that was located at the upstream area and the middle section of the river. As a yard meant for servicing small boats, used engine oil may overflow from the docks, and this can cause high levels of Pb concentration in the sampling stations. In another research conducted by Woolf, et al. (2007), it was stated that Pb content in sediment may be due to broken-down lead paint, residues from lead-containing gasoline, used engine oil, or pesticides used in the past, contaminated landfills, or nearby industries such as foundries or smelters 39. Other than Pb, Cu was also in the spotlight.

 

Based on these studies, the weak correlation (p > 0.05) for both Cu and As with OM content in sediment indicates that OM was not a major factor in controlling Cu and As distribution. This weak correlation may be the result of complex geochemical reactions where it is not as easy as sedimentation process 40. Furthermore, the environmental conditions of the river such as discharges of upstream pollutants, and alternation between fresh water and seawater may be very complicated that it resulted in very little correlation between these metals and OM content.

To get a better understanding, Multivariate Analyses (Principle Component Analysis) was carried out (Figure 6). The factor loadings or component loadings are the correlation between variables Coefficients and factors. The squared factor loading is the percent of variance in a variable cans that's be explained by a factor. According to Figure 6, all metals and OM were focused on the first PC (PC1, variance of 68%) compared to the second PC (PC2, variance of 14%).  PC1can be defined as an anthropogenic component due to its high-variability observed in the present study.

Figure 6 Principal component analysis loading plots for the components

For the purposes to assess the anthropogenic sources, the SQG have been used for the assessment of the degree of sediment contamination (Table 5) in the study area. Threshold effect levels (TEL) and probable effect level (PEL) were proposed by CCME in which the TEL, represents the concentration below which adverse biological effects are expected to occur rarely 41. The upper value, referred to PEL, defines the level above which adverse effects are expected to occur frequently. Furthermore, another approach to characterize contamination in sediment by Long et al. (1995) was by using effective range-long (ERL) and effective range median (ERM) 42. Metal concentrations below the ERL value are not expected to elicit adverse effects, while levels above the ERM value are likely to be very toxic.

Table 5 Background and sediment quality guideline value

a: Average shale values by Wedepohl, 199543, b: Sediment Quality Guideline (SQG) by CCME: Canadian Council of Ministers of the Environment; Canadian Sediment Quality Guidelines for the Protection of Aquatic Life (2002) 41, c: Effective Range-Low (ERL) and Effective Range-Median (ERM) by Long, et al., 1995 42.

a. Average shale values by Wedepohl, 1995. b. Sediment Quality Guideline (SQG) by CCME: Canadian Council of Ministers of the Environment; Canadian Sediment Quality Guidelines for the Protection of Aquatic Life (2002). c. Effective Range-Low (ERL) and Effective Range-Median (ERM) by Long, et al., 1995.

As a comparison of the heavy metals concentrations within sediment quality guideline (SQG), the concentrations of all metals except Cd and Zn in sediment of Sungai Perlis were above the Threshold Effect Level (TEL). In contrast, only As at St 9 (77.50 mg/kg dry weight) and St 10 (59.12 mg/kg dry weight) during NE monsoon exceed the limit of PEL. Thus, the concentration for Arsenic (As) may be considered as a serious threat for aquatic organism and St 10 (59.12 mg/kg dry weight) during NE monsoon exceed the limit of PEL. Thus, the concentration for Arsenic (As) may be considered as a serious threat for aquatic organism and human being health. According to Allen (2002), sediment quality guidelines are very useful to screen sediment contamination by comparing sediment contaminant concentration with the corresponding quality guideline 44.

Conclusions

From this study, the overall trend of mean concentration of heavy metals in Sungai Perlis can be concluded by the following order; Zn > Cr > Pb > Cu > As > Cd during the SWM season, and Cr > Zn > Pb > As > Cu > Cd during the NEM season. The percentage of organic matter content (OM) of sediment was slightly higher during the SWM season. According to Pearson’s correlation analysis, all elements have a significant relationship (p<0.05) between heavy metal and OM, except for As and Cu. From this study, it can be concluded that aquaculture wastes, domestic sewage and paddy wastes do influence the distribution of heavy metals and OM percentage. According to Principal component analysis, all metals can be defined as an anthropogenic component, However, the sediment quality guidelines (SQG) proved that, Cd and Zn in sediment of Sungai Perlis were below from the threshold values. While, the concentrations of Arsenic from this study area may be considered as a serious threat for aquatic organism and also human health. In the future, a study for the relationship between aquatic organism and metals pollution should be done in attempts to quantify the health impact of heavy metals to the river system in this area.

Acknowledgements

This research was conducted under the funding of Malaysia Ministry of Higher Education (MOHE) and University Teknologi MARA (UiTM) , through the Fundamental Research Grant Scheme (FRGS) -600-RMI/ST/FRGS 5/3/Fst (284/2010). The authors wish to express their gratitude to the ceanography Laboratory team members for their invaluable assistance and hospitality throughout the sampling period.

Author Contributions

Jamil T: As a leader for this project, marine geochemistry expert.
Lias K: Analytical Chemist, environmental chemistry expert
Hanif HF: Postgraduate Student under this Grant Scheme
Norsila D: Statistical Expert
Aeisyah A: Undergraduate Student under this Grant Scheme
Kamaruzzaman BY: Research Collaborator

References

  1. Eldemerdash FM, Elegamy EL (1999) Biological effects in Tilapia nilotica fish as indicators of pollution by cadmio and mercury. International Journal of Environmental Health Research 9: pp. 173-186.
  2. Luoma SN (1983) Bioavailability of trace metals to aquatic organisms A review. The Science of the Total Environment 28: pp. 1-22. doi: 10.1016/S0048-9697(83)80004-7
  3. Feng L, Wen YM, Zhu PT (2008) Bioavailability and Toxicity of Heavy Metals in a Heavily Polluted River, in PRD, China. Bulletin of Environmental Contamination and Toxicology 81: pp. 90-94.
  4. Kim MJ, KH Ahn and Y Jung (2002) Distribution of inorganic arsenic species in mine tailings of abundance mine from Korea. Chemosphere 49: pp. 307-312.
  5. Lee CG, H Chon and MC Jung (2001) Heavy metals contamination in the vicinity of Daduk Au-Ag-Pb-Zn mine in Korea. Applied Geochem 16: pp. 1377-1386.
  6. Mustafa S and Nilgun DE (2006) Copper (II)-rubeanic acid coprecipitation system for separation-preconcentration of trace metal ions in environmental samples for their flame atomic absorption spectrometric determinations. Journal of Hazardous Materials 137: pp. 1035-1041.
  7. Vertacnik A, Prohic E, Kozar S, Juracic M (1995) Behavior of some trace elements in alluvial sediments, Zagreb water-well field area, Croatia. Water Research 29: pp. 237-246. doi:10.1016/0043-1354(94)E0114-L.
  8. Berner RA (1982) Burial of organic carbon and pyrite sulfur in the modern ocean: its geochemical and environmental significance. American Journal of Science 282: pp. 451- 473.
  9. Means JC, Wood SG, Hassett JJ & Banwart WL (1980) Sorption of polynuclear aromatic hydrocarbons by sediments and soils. Environmental Science & Technology 14: pp.1524-1528. doi: 10.1021/es60172a005.
  10. Tsai PP, Stelzer HD, Hedrich HJ, Hackbarth H (2003) Are the effects of different enrichment designs on the physiology and behaviour of DBA/2 mice consistent? Laboratory Animals 37 : pp. 314-327. doi: 10.1258/002367703322389889.
  11. González F, A Vargas, JM Arias and E Montoya (1991) Phosphatase activity during development cycle of Myxococcus xanthus. Canadian Journal of Microbiology 37: pp. 74-77.
  12. Wang F, Chen J (2000) Relation of sediment characteristics to trace metal concentrations: a statistical study. Water Research l (4): pp. 694-698. doi: 10.1016/S0043-1354(99)00184-0.
  13. Katz A, IR Kaplan (1981) Heavy metals behavior in coastal sediments of southern California: a critical review and synthesis. Marine Chemistry 10: pp. 261-299. doi: 10.1016/0304-4203(81)90010-4.
  14. Tsugonai S, Yamada M (1980) 226Ra in Bering sea sediment and its application as a geochronometer. Geochemical Journal 13: pp. 231-238.
  15. Kamaruzzaman BY (1999) Geochemistry or the marine sediments. Its paleoceanographic significance. Ph.D Thesis. Hokkaido University: p. 143.
  16. Jamil T (2006) Physicochemical and sediment characteristics of the bottom sediment of Terengganu River, Terengganu Malaysia. M.Sc. Thesis. Kolej Universiti Sains dan Teknologi Malaysia.
  17. Trimm DL, Beiro HH and Parker SJ (1998) Comparison of Digestion Techniques in Analyses for Total Metals in Marine Sediment. Bulletin of Environmental Contamination and Toxicology 60: pp. 425-432. doi:10.1007/s001289900643.
  18. Chen M, Ma LQ (2001) Comparison of Three Aqua Regia Digestion Methods for Twenty Florida Soils. Soil Science Society of America Journal 65: pp. 491-499. doi: 10.2136/sssaj2001.652491x.
  19. Macalady DL, Ranville JF (1998) The chemistry and geochemistry of natural organic matter. In: Macalady DL (ed.) Perspectives in Environmental Chemistry, Chapter 5, Oxford University Press, New York, pp. 94-137. ISBN-13: 978-0195102086.
  20. Meybeck M (1982) Carbon, nitrogen and phosphorus transport by world rivers. American Journal of Science 282: pp. 401-450. doi: 10.2475/ajs.282.4.401.
  21. Degens ET, Kempe S, Richey JE (1991) Biogeochemistry of major world rivers, summary. In:  Degens ET, Kempe S, Richey JE (eds) Biogeochemistry of Major World Rivers, SCOPE 42. J Wiley and Sons, New York, pp. 323-347. doi: 10.1002/aqc.3270010209.
  22. Xing L, Zhang H, Yuan Z, Sun Y, Zao M (2011) Terrestrial and marine biomarker estimates of organic matter sources and distributions in surface sediments from the East China Sea shelf. Continental Shelf Research 31: pp. 1106-1115. doi: 10.1016/j.csr.2011.04.003.
  23. Price NB (1976) Chemical diagenesis in sediment. In: Riley JP, Chester R (Eds.) Chemical Oceanography 6, 2nd Edition. Academic Press, New York, pp. 1-58. doi: 10.1016/B978-0-12-588606-2.50011-4.
  24. Yu KC, LJ Tsai, SH Chen and ST Ho (2001) Correlation analysis on binding behaviour of heavy metals with sediment matrices. Water Research 4: pp. 2417-2428.
  25. Veeh HH (1967) Deposition of uranium from the ocean. Earth and planetary science letters 3: pp. 145-150. doi: 10.1016/0012-821X(67)90026-X.
  26. Jones GB (1974) Molybdenum in a nearshore and etuarine environment, North wales. Estuarine and Coastal marine Science 2: pp. 185-189. doi: 10.1016/0012-821X(67)90026-X.
  27. Chou CL, K Haya, LA Paon, L Burridge, and JD Moffatt (2002) Aquaculture-related trace metals in sediments and lobsters and relevance to environmental monitoring program ratings (EMP) for near-field effects. Marine Pollution Bulletin 44 (11): pp. 1259-1269.
  28. Burridge LE, K Doe, K Haya, PM Jackman, G Lindsay and V Zitko (1999) Chemical analysis and toxicity tests on sediments under salmon net pens in the Bay of Fundy. Canadian Technical Report of Fisheries and Aquatic Sciences 2291 (3): p. 39.
  29. Agency for Toxic Substances and Disease Registry-ATSDR (2005) Zinc Toxicity. Case Studies in Environmental Medicine (CSEM): p. 159.
  30. Finnish Ministry of Agriculture and Forestry (2000) Cadmium In Fertilizers: Risks To Human Health And The Environment.
  31. Lu RK, Shi ZY, Xiong LM (1992) Cadmium contents of rock phosphates and phosphate fertilizers of China and their effects on ecological environment. Acta Pedologica Sinica 29: pp. 150-157.
  32. Zarcinas BA, Pongsakul P, McLaughlin MJ, Gill Cozens (2004) Heavy metals in soils and crops in south-east Asia: 1. Peninsular Malaysia. Environmental Geochemistry and Health 26: pp. 343-357.
  33. Jamil H, Theng LP, Jusoh K, Razali AM, Ali FB and Ismail BS (2011) Speciation of heavy metals in paddy soils from selected areas in Kedah and Penang, Malaysia. African Journal of Biotechnology 10 (62): pp. 13505-13513. doi: 10.5897/AJB11.225.
  34. Genesio Circosta Ä (2011) Gold (and Copper) Exploration and Mining Potential of the Loei – Phetchabun Volcanic Belt International Conference on Geology, Geotechnology and Mineral Resources of Indochina (GEOINDO 2011) 1-3, Khon Kaen, Thailand.
  35. Price L (2011) Tin Mining in the Limestone Caves of Perlis, Malaysia. Acta Carsologica 40 (3): pp. 497 – 503. doi: 10.3986/ac.v40i3.63.
  36. EIP Associates (1999) Zinc Source Identification. Prepared for Palo Alto Regional Water Quality Control Plant.
  37. Agency for Toxic Substances and Disease Registry-ATSDR (2008) Chromium Toxicity. Case Studies in Environmental Medicine (CSEM): p. 67.
  38. Barceloux DG (1999) Chromium. Clinical Toxicology 37: pp. 173-194. doi: 10.1081/CLT-100102418.
  39. Woolf AD, Goldman R, Bellinger DC (2007) Update on the clinical management of childhood lead poisoning. Pediatric clinics of North America 54 (2): pp. 271-294. doi: 10.1016/j.pcl.2007.01.008.
  40. Morse JW, Presley BJ, Taylor RJ, Benoit G, Santschi P (1993) Trace metal chemistry of Galveston Bay: Water sediments and biota. Marine Environmental Research 36: pp. 1-37. doi: 10.1016/0141-1136(93)90087-G.
  41. Canadian Councils of Ministers of the Environment (CCME) (2002) Canadian water quality guidelines for the protection of aquatic life. Canadian Water Quality Index 1.0, Technical Report, Winnipeg, Canada: pp. 29-36.
  42. Long ER, MacDonald DD, Smith SL and Calder FD (1995) Incidence of adverse biological effects within ranges of chemical concentrations in marine and estuarine sediments.  Environmental Management 19 (1): pp. 81-97. doi: 10.1007/BF02472006.
  43. Wedepohl KH (1995) The composition of the continental crust. Geochimica et Cosmochimica Acta 59 (7): pp. 1217-1232. doi: 10.1007/BF01829361.
  44. Allen G (2002) Sediment quality criteria in use around the world. Limnology 3: pp. 65–76.
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